scholarly journals Multi-Frequency Based Direction-of-Arrival Estimation for 2q-Level Nested Radar & Sonar Arrays

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3385 ◽  
Author(s):  
Hao Zhou ◽  
Guoping Hu ◽  
Junpeng Shi ◽  
Ziang Feng
Keyword(s):  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Research Area ◽  
Frequency Separation ◽  
Frequency Method ◽  
Virtual Sensors ◽  
Order Difference ◽  
Sonar Systems ◽  
Minimum Number

Direction finding is a hot research area in radar and sonar systems. In the case of q ≥ 2, the 2qth-order cumulant based direction of arrival (DOA) estimation algorithm for the 2q-level nested array can achieve high resolution performance. A virtual 2qth-order difference co-array, which contains O(N2q) virtual sensors in the form of a uniform linear array (ULA), is yielded and the Gaussian noise is eliminated. However, some virtual elements are separated by the holes among the 2qth-order difference co-array and cannot be fully used. Even though the application of the multi-frequency method for minimum frequency separation (MFMFS) can fill the holes with low computation complexity, it requires that the number of frequencies must increase with the number of holes. In addition, the signal spectra have to be proportional for all frequencies, which is hard to satisfy when the number of holes is large. Aiming at this, we further propose a multi-frequency method for a minimum number of frequencies (MFMNF) and discuss the best frequency choice under two specific situations. Simulation results verify that, compared with the MFMFS method, the proposed MFMNF method can use only one frequency to fill all the holes while achieving a longer virtual array and the DOA estimation performance is, therefore, improved.

scholarly journals Minimum Array Elements for Resolution of Several Direction of Arrival Estimation Methods in Various Noise-Level Environments

2018 ◽  
Vol 2 ◽  
pp. 87-94
Author(s):  
Ismail El Ouargui ◽  
Said Safi ◽  
Miloud Frikel
Keyword(s):  
Gaussian Noise ◽  
Noise Level ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Minimum Number ◽  
Informative Signals

The resolution of a Direction of Arrival (DOA) estimation algorithm is determined based on its capability to resolve two closely spaced signals. In this paper, authors present and discuss the minimum number of array elements needed for the resolution of nearby sources in several DOA estimation methods. In the real world, the informative signals are corrupted by Additive White Gaussian Noise (AWGN). Thus, a higher signal-to-noise ratio (SNR) offers a better resolution. Therefore, we show the performance of each method by applying the algorithms in different noise level environments.

scholarly journals An Enhanced Smoothed L0-Norm Direction of Arrival Estimation Method Using Covariance Matrix

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4403
Author(s):  
Ji Woong Paik ◽  
Joon-Ho Lee ◽  
Wooyoung Hong
Keyword(s):  
Covariance Matrix ◽  
Phased Array ◽  
Null Space ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Improve Performance ◽  
Space Projection

An enhanced smoothed l0-norm algorithm for the passive phased array system, which uses the covariance matrix of the received signal, is proposed in this paper. The SL0 (smoothed l0-norm) algorithm is a fast compressive-sensing-based DOA (direction-of-arrival) estimation algorithm that uses a single snapshot from the received signal. In the conventional SL0 algorithm, there are limitations in the resolution and the DOA estimation performance, since a single sample is used. If multiple snapshots are used, the conventional SL0 algorithm can improve performance in terms of the DOA estimation. In this paper, a covariance-fitting-based SL0 algorithm is proposed to further reduce the number of optimization variables when using multiple snapshots of the received signal. A cost function and a new null-space projection term of the sparse recovery for the proposed scheme are presented. In order to verify the performance of the proposed algorithm, we present the simulation results and the experimental results based on the measured data.

scholarly journals A Direction-of-Arrival Estimation Algorithm Based on Compressed Sensing and Density-Based Spatial Clustering and Its Application in Signal Processing of MEMS Vector Hydrophone

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2191
Author(s):  
Huichao Yan ◽  
Ting Chen ◽  
Peng Wang ◽  
Linmei Zhang ◽  
Rong Cheng ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Spatial Clustering ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Cluster Center ◽  
Direction Of Arrival Estimation ◽  
Vector Hydrophone ◽  
Regularization Parameters ◽  
Selection Of

Direction of arrival (DOA) estimation has always been a hot topic for researchers. The complex and changeable environment makes it very challenging to estimate the DOA in a small snapshot and strong noise environment. The direction-of-arrival estimation method based on compressed sensing (CS) is a new method proposed in recent years. It has received widespread attention because it can realize the direction-of-arrival estimation under small snapshots. However, this method will cause serious distortion in a strong noise environment. To solve this problem, this paper proposes a DOA estimation algorithm based on the principle of CS and density-based spatial clustering (DBSCAN). First of all, in order to make the estimation accuracy higher, this paper selects a signal reconstruction strategy based on the basis pursuit de-noising (BPDN). In response to the challenge of the selection of regularization parameters in this strategy, the power spectrum entropy is proposed to characterize the noise intensity of the signal, so as to provide reasonable suggestions for the selection of regularization parameters; Then, this paper finds out that the DOA estimation based on the principle of CS will get a denser estimation near the real angle under the condition of small snapshots through analysis, so it is proposed to use a DBSCAN method to process the above data to obtain the final DOA estimate; Finally, calculate the cluster center value of each cluster, the number of clusters is the number of signal sources, and the cluster center value is the final DOA estimate. The proposed method is applied to the simulation experiment and the micro electro mechanical system (MEMS) vector hydrophone lake test experiment, and they are proved that the proposed method can obtain good results of DOA estimation under the conditions of small snapshots and low signal-to-noise ratio (SNR).

scholarly journals Novel Diagonal Reloading Based Direction of Arrival Estimation in Unknown Non-Uniform Noise

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Hao Zhou ◽  
Guoping Hu ◽  
Junpeng Shi ◽  
Ziang Feng
Keyword(s):  
Covariance Matrix ◽  
Degrees Of Freedom ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Main Diagonal ◽  
Sample Covariance ◽  
Uniform Noise ◽  
Negative Effect ◽  
Signal Covariance Matrix

Nested array can expand the degrees of freedom (DOF) from difference coarray perspective, but suffering from the performance degradation of direction of arrival (DOA) estimation in unknown non-uniform noise. In this paper, a novel diagonal reloading (DR) based DOA estimation algorithm is proposed using a recently developed nested MIMO array. The elements in the main diagonal of the sample covariance matrix are eliminated; next the smallest MN-K eigenvalues of the revised matrix are obtained and averaged to estimate the sum value of the signal power. Further the estimated sum value is filled into the main diagonal of the revised matrix for estimating the signal covariance matrix. In this case, the negative effect of noise is eliminated without losing the useful information of the signal matrix. Besides, the degrees of freedom are expanded obviously, resulting in the performance improvement. Several simulations are conducted to demonstrate the effectiveness of the proposed algorithm.

scholarly journals An Improved Two-Dimensional Direction-Of-Arrival Estimation Algorithm for L-Shaped Nested Arrays with Small Sample Sizes

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2176 ◽  
Author(s):  
Xiaofeng Gao ◽  
Xinhong Hao ◽  
Ping Li ◽  
Guolin Li
Keyword(s):  
Correlation Matrix ◽  
Degrees Of Freedom ◽  
Full Rank ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Covariance Matrices ◽  
Small Sample ◽  
Two Dimensional ◽  
Nested Arrays

In this paper, an improved two-dimensional (2-D) direction of arrival (DOA) estimation algorithm for L-shaped nested arrays is proposed. Unlike the approach for a classical nested array, which use the auto-correlation matrix (ACM) to increase the degrees of freedom (DOF), we utilize the cross-correlation matrix (CCM) of different sub-arrays to generate two long consecutive virtual arrays. These acquire a large number of DOF without redundant elements and eliminate noise effects. Furthermore, we reconstruct the CCM based on the singular value decomposition (SVD) operation in order to reduce the perturbation of noise for small numbers of samples. To cope with the matrix rank deficiency of the virtual arrays, we construct the full rank equivalent covariance matrices by using the output and its conjugate vector of virtual arrays. The unitary estimation of signal parameters via rotational invariance technique (ESPRIT) is then performed on the covariance matrices to obtain the DOA of incident signals with low computational complexity. Finally, angle pairing is achieved by deriving the equivalent signal vector of the virtual arrays using the estimated angles. Numerical simulation results show that the proposed algorithm not only provides more accurate 2-D DOA estimation performance with low complexity, but also achieves angle estimation for small numbers of samples compared to existing similar methods.

scholarly journals Two-Dimensional Direction of Arrival (DOA) Estimation for Rectangular Array via Compressive Sensing Trilinear Model

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Huaxin Yu ◽  
Xiaofeng Qiu ◽  
Xiaofei Zhang ◽  
Chenghua Wang ◽  
Gang Yang
Keyword(s):  
Compressive Sensing ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Two Dimensional ◽  
Rectangular Array ◽  
Angle Estimation ◽  
Estimation Performance ◽  
Trilinear Model ◽  
2D Doa Estimation

We investigate the topic of two-dimensional direction of arrival (2D-DOA) estimation for rectangular array. This paper links angle estimation problem to compressive sensing trilinear model and derives a compressive sensing trilinear model-based angle estimation algorithm which can obtain the paired 2D-DOA estimation. The proposed algorithm not only requires no spectral peak searching but also has better angle estimation performance than estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. Furthermore, the proposed algorithm has close angle estimation performance to trilinear decomposition. The proposed algorithm can be regarded as a combination of trilinear model and compressive sensing theory, and it brings much lower computational complexity and much smaller demand for storage capacity. Numerical simulations present the effectiveness of our approach.

scholarly journals DOA Estimation of Wideband Cyclic MUSIC Algorithm under Rayleigh Fading Environment in MIMO Systems

2020 ◽  
Vol 9 (1) ◽  
pp. 1834-1837
Keyword(s):  
High Resolution ◽  
Rayleigh Fading ◽  
Array Signal Processing ◽  
Mimo Systems ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Direction Of Arrival Estimation ◽  
Music Algorithm

Direction of arrival (DOA) estimation has, for quite some time been a challenging situation in most of the wireless communication applications, radar and sonar. The resolution of the direction of arrival estimation can be increased using the help of array signal processing. The performance of the direction of arrival estimation for multiple input multiple output(MIMO) radar systems has been reviewed for cyclic Multiple Signal Classification(MUSIC), extended cyclic MUSIC and Wideband cyclic MUSIC under Rayleigh fading environment. MUSIC and its variants have been taken into consideration for the analysis as these have been a very good parameter estimation technique due its low cost, high resolution and stability. Direction of Arrival estimation clubbed with cyclostationarity has been included into the new algorithm because of its immunity to noise and interference. The new algorithm along with cyclic correlations when applied to these signals, improves the performance of the entire system substantially. The performance of this wideband cyclic MUSIC high resolution direction of arrival estimation algorithm over the Rayleigh fading is analyzed in this paper. The simulation results citing the three methods show the performance of these methods in presence of the fading environments.

scholarly journals Blind Direction-of-Arrival Estimation with Uniform Circular Array in Presence of Mutual Coupling

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Song Liu ◽  
Lisheng Yang ◽  
Shizhong Yang ◽  
Qingping Jiang ◽  
Haowei Wu
Keyword(s):  
Mutual Coupling ◽  
Coupling Parameter ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Estimation Methods ◽  
Circular Array ◽  
Signal Parameters ◽  
Simulation Results ◽  
Parameter Estimation Methods

A blind direction-of-arrival (DOA) estimation algorithm based on the estimation of signal parameters via rotational invariance techniques (ESPRIT) is proposed for a uniform circular array (UCA) when strong electromagnetic mutual coupling is present. First, an updated UCA model with mutual coupling in a discrete Fourier transform (DFT) beam space is deduced, and the new manifold matrix is equal to the product of a centrosymmetric diagonal matrix and a Vandermonde-structure matrix. Then we carry out blind DOA estimation through a modified ESPRIT method, thus avoiding the need for spatial angular searching. In addition, two mutual coupling parameter estimation methods are presented after the DOAs have been estimated. Simulation results show that the new algorithm is reliable and effective especially for closely spaced signals.

Battlefield Acoustic Target Localization in Electronic Sentinel System

2012 ◽  
Vol 490-495 ◽  
pp. 1348-1352
Author(s):  
Guang Yu Liu ◽  
Cheng Zhang ◽  
Tie Lin Liu
Keyword(s):  
High Resolution ◽  
Direction Of Arrival ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Target Localization ◽  
Circular Array ◽  
Rigid Cylinder ◽  
Localization Algorithms ◽  
Acoustic Target

The problem of battlefield acoustic target localization is studied based on an array model of a uniform circular array (UCA) mounted on a rigid cylinder including beamforming technology and high resolution direction of arrival (DOA) estimation algorithm. The influence of various facts to the discussed localization algorithms is analyzed. It is concluded that the direction of the battlefield acoustic target can be achieved by the proposed high resolution DOA estimation algorithm. The performance of the eigen-beam beamforming array and the high resolution DOA estimation algorithm can be improved by the rigid cylinder.

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